Systems and methods for determining correction parameters for imaging devices

ABSTRACT

Systems and methods for determining at least one correction parameter for a Positron Emission Tomography (PET) scanner including a plurality of detector units is provided. For each of the plurality of detector units, the methods may include determining, based on scan data of one or more scans of a phantom at a plurality of positions, a first sum of coincidence events detected by the detector unit. The methods may further include determining a second sum of coincidence events that are expected to be detected by the detector unit and determining, based on the first sum of coincidence events and the second sum of coincidence events, at least one correction parameter associated with the detector unit. The phantom may be moved to the plurality of positions along an axis of a field of view of the PET scanner during the one or more scans.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to Chinese Patent Application No.201910390320.5 filed on May 10, 2019, the entire contents of which arehereby incorporated by reference.

TECHNICAL FIELD

The present disclosure generally relates to imaging devices, and moreparticularly, relates to systems and methods for determining one or morecorrection parameters for imaging devices, such as a Positron EmissionTomography (PET) scanner.

BACKGROUND

Positron Emission Tomography (PET) is a noninvasive nuclear medicalimaging technique that is widely used for diagnostic analysis. In orderto decrease artifacts in a PET image, there is a need for anormalization correction for the detection efficiency of detectors inthe PET system and the detection efficiency of lines of response (LORs)of the detectors. In existing methods for normalization correction, aphantom is often used. The length of the phantom needs to cover theaxial field of view (FOV) of the PET scanner so that gamma light ofapproximately the same intensity is emitted and then measured by thedetectors. For a PET scanner with a relatively long axial FOV (e.g.,such as a whole-body PET scanner that has an axial FOV of or close to 2meters), a relatively long phantom is needed. There may be problems intransporting and/or storing such a long phantom. Moreover, it may beinconvenient for an operator to maneuver such a long phantom in ascanning of the phantom using the PET scanner. Furthermore, it may bedifficult to manufacture a phantom of such a length. Therefore, it isdesired to develop more convenient systems and methods for determiningone or more correction parameters for PET scanners.

SUMMARY

According to an aspect of the present disclosure, a system fordetermining at least one correction parameter for a Positron EmissionTomography (PET) scanner including a plurality of detector units isprovided. The system may include at least one non-transitory storagemedium including a set of instructions and at least one processor incommunication with the at least one non-transitory storage medium. Whenexecuting the set of instructions, for each of the plurality of detectorunits, the at least one processor may be configured to cause the systemto perform operations including: determining, based on scan data of oneor more scans of a phantom at a plurality of positions, a first sum ofcoincidence events detected by the detector unit. The phantom may bemoved to the plurality of positions along an axis of a field of view ofthe PET scanner during the one or more scans, and a length of thephantom may be less than a length of the field of view of the PETscanner along the axis. The operations may further include determining asecond sum of coincidence events that are expected to be detected by thedetector unit, and determining, based on the first sum of coincidenceevents and the second sum of coincidence events, at least one correctionparameter associated with the detector unit.

In some embodiments, to determine the first sum of coincidence events,the at least one processor may be configured to cause the system toperform operations including: obtaining the scan data of the one or morescans of the phantom at the plurality of positions; for each of theplurality of positions, determining, based on the scan data, a firstcount of detected coincidence events that are detected by the detectorunit; and determining the first sum of coincidence events based on thefirst count of detected coincidence events for each of the plurality ofpositions.

In some embodiments, to determine the second sum of coincidence events,the at least one processor may be configured to cause the system toperform operations including: for each of the plurality of positions,determining a second count of coincidence events that are expected to bedetected by the detector unit based on geometric parameters of thephantom, position information of the phantom, and a scanning period ofthe phantom at the position; and determining the second sum ofcoincidence events based on the second count of coincidence events foreach of the plurality of positions.

In some embodiments, the phantom may be moved to the plurality ofpositions in a step-wise mode, and a moving distance for each movementof the phantom may be less than the length of the phantom.

In some embodiments, the phantom may be continuously moved to theplurality of positions.

In some embodiments, the phantom may be continuously moved to theplurality of positions at a constant speed.

In some embodiments, to determine the first sum of coincidence events,the at least one processor may be configured to cause the system toperform operations including performing one or more corrections on thescan data of the one or more scans of the phantom at the plurality ofpositions to obtain corrected scan data; and determining the first sumof coincidence events based on the corrected scan data. The one or morecorrections may include at least one of an attenuation correction, adead-time correction, a random coincidence correction, or a scattercorrection.

In some embodiments, the at least one correction parameter may includean axial block profile, and to determine the at least one correctionparameter, the at least one processor may be configured to cause thesystem to perform operations including determining the axial blockprofile associated with the PET scanner based on the first sum ofcoincidence events and the second sum of coincidence events.

In some embodiments, the at least one correction parameter may include aplane efficiency, and to determine the at least one correctionparameter, the at least one processor may be configured to cause thesystem to perform operations including: obtaining a first corrected sumof coincidence events by correcting the first sum of coincidence eventsusing the axial block profile for each detector unit, and determiningthe plane efficiency associated with the PET scanner based on the firstcorrected sum of coincidence events and the second sum of coincidenceevents.

In some embodiments, the at least one correction parameter may include atransverse block profile, and to determine the at least one correctionparameter, the at least one processor may be further configured to causethe system to perform operations including obtaining a second correctedsum of coincidence events by correcting the first corrected sum ofcoincidence events using the plane efficiency for each detector unit,and determining the transverse block profile associated with the PETscanner based on the second corrected sum of coincidence events and thesecond sum of coincidence events.

In some embodiments, the at least one correction parameter may include acrystal efficiency, and to determine the at least one correctionparameter, the at least one processor may be configured to cause thesystem to perform operations including: obtaining a third corrected sumof coincidence events by correcting the second corrected sum ofcoincidence events using the transverse block profile for each detectorunit, and determining the crystal efficiency associated with the PETscanner based on the third corrected sum of coincidence events and thesecond sum of coincidence events.

According to another aspect of the present disclosure, a method fordetermining at least one correction parameter for a Positron EmissionTomography (PET) scanner including a plurality of detector units isprovided. The method may be implemented on a computing device having atleast one processor and at least one non-transitory storage medium. Foreach of the plurality of detector units, the method may includedetermining, based on scan data of one or more scans of a phantom at aplurality of positions, a first sum of coincidence events detected bythe detector unit. The method may further include determining a secondsum of coincidence events that are expected to be detected by thedetector unit and determining, based on the first sum of coincidenceevents and the second sum of coincidence events, at least one correctionparameter associated with the detector unit. The phantom may be moved tothe plurality of positions along an axis of a field of view of the PETscanner during the one or more scans, and a length of the phantom may beless than a length of the field of view of the PET scanner along theaxis.

According to yet another aspect of the present disclosure, anon-transitory computer readable medium is provided. The non-transitorycomputer readable medium may include at least one set of instructions.When executed by at least one processor of a computing device, the atleast one set of instructions may direct the at least one processor toperform operations including: for each of the plurality of detectorunits, determining, based on scan data of one or more scans of a phantomat a plurality of positions, a first sum of coincidence events detectedby the detector unit; determining a second sum of coincidence eventsthat are expected to be detected by the detector unit; and determining,based on the first sum of coincidence events and the second sum ofcoincidence events, at least one correction parameter associated withthe detector unit. The phantom may be moved to the plurality ofpositions along an axis of a field of view of the PET scanner during theone or more scans, and a length of the phantom may be less than a lengthof the field of view of the PET scanner along the axis

Additional features will be set forth in part in the description whichfollows, and in part will become apparent to those skilled in the artupon examination of the following and the accompanying drawings or maybe learned by production or operation of the examples. The features ofthe present disclosure may be realized and attained by practice or useof various aspects of the methodologies, instrumentalities, andcombinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplaryembodiments. These exemplary embodiments are described in detail withreference to the drawings. The drawings are not to scale. Theseembodiments are non-limiting exemplary embodiments, in which likereference numerals represent similar structures throughout the severalviews of the drawings, and wherein:

FIG. 1 is a schematic diagram illustrating an exemplary imaging systemaccording to some embodiments of the present disclosure;

FIG. 2 is a schematic diagram illustrating exemplary hardware and/orsoftware components of an exemplary computing device according to someembodiments of the present disclosure;

FIG. 3 is a schematic diagram illustrating exemplary hardware and/orsoftware components of an exemplary terminal device according to someembodiments of the present disclosure;

FIG. 4 is a block diagram illustrating an exemplary PET scannercorrection device according to some embodiments of the presentdisclosure;

FIG. 5 is a block diagram illustrating an exemplary PET scannercorrection device according to some embodiments of the presentdisclosure;

FIG. 6 is a flowchart illustrating an exemplary process for determiningat least one correction parameter according to some embodiments of thepresent disclosure;

FIG. 7 a flowchart illustrating an exemplary process for determining anactual sum of coincidence events according to some embodiments of thepresent disclosure;

FIG. 8 is a flowchart illustrating an exemplary process for determininga reference sum of coincidence events according to some embodiments ofthe present disclosure; and

FIG. 9 is a flowchart illustrating an exemplary process for determiningat least one correction parameter according to some embodiments of thepresent disclosure.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth by way of examples in order to provide a thorough understanding ofthe relevant disclosure. However, it should be apparent to those skilledin the art that the present disclosure may be practiced without suchdetails. In other instances, well-known methods, procedures, systems,components, and/or circuitry have been described at a relativelyhigh-level, without detail, in order to avoid unnecessarily obscuringaspects of the present disclosure. Various modifications to thedisclosed embodiments will be readily apparent to those skilled in theart, and the general principles defined herein may be applied to otherembodiments and applications without departing from the spirit and scopeof the present disclosure. Thus, the present disclosure is not limitedto the embodiments shown, but to be accorded the widest scope consistentwith the claims.

The terminology used herein is for the purpose of describing particularexample embodiments only and is not intended to be limiting. As usedherein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprise,”“comprises,” and/or “comprising,” “include,” “includes,” and/or“including,” when used in this specification, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof.

It will be understood that the term “system,” “engine,” “unit,”“module,” and/or “block” used herein are one method to distinguishdifferent components, elements, parts, sections or assembly of differentlevels in ascending order. However, the terms may be displaced byanother expression if they achieve the same purpose.

Generally, the word “module,” “unit,” or “block,” as used herein, refersto logic embodied in hardware or firmware, or to a collection ofsoftware instructions. A module, a unit, or a block described herein maybe implemented as software and/or hardware and may be stored in any typeof non-transitory computer-readable medium or other storage device. Insome embodiments, a software module/unit/block may be compiled andlinked into an executable program. It will be appreciated that softwaremodules can be callable from other modules/units/blocks or fromthemselves, and/or may be invoked in response to detected events orinterrupts. Software modules/units/blocks configured for execution oncomputing devices (e.g., processor as illustrated in FIG. 2) may beprovided on a computer-readable medium, such as a compact disc, adigital video disc, a flash drive, a magnetic disc, or any othertangible medium, or as a digital download (and can be originally storedin a compressed or installable format that needs installation,decompression, or decryption prior to execution). Such software code maybe stored, partially or fully, on a storage device of the executingcomputing device, for execution by the computing device. Softwareinstructions may be embedded in firmware, such as an EPROM. It will befurther appreciated that hardware modules/units/blocks may be includedin connected logic components, such as gates and flip-flops, and/or canbe included of programmable units, such as programmable gate arrays orprocessors. The modules/units/blocks or computing device functionalitydescribed herein may be implemented as software modules/units/blocks butmay be represented in hardware or firmware. In general, themodules/units/blocks described herein refer to logicalmodules/units/blocks that may be combined with othermodules/units/blocks or divided into sub-modules/sub-units/sub-blocksdespite their physical organization or storage. The description may beapplicable to a system, an engine, or a portion thereof.

It will be understood that when a unit, engine, module or block isreferred to as being “on,” “connected to,” or “coupled to,” anotherunit, engine, module, or block, it may be directly on, connected orcoupled to, or communicate with the other unit, engine, module, orblock, or an intervening unit, engine, module, or block may be presentunless the context clearly indicates otherwise. As used herein, the term“and/or” includes any and all combinations of one or more of theassociated listed items.

These and other features, and characteristics of the present disclosure,as well as the methods of operation and functions of the relatedelements of structure and the combination of parts and economies ofmanufacture, may become more apparent upon consideration of thefollowing description with reference to the accompanying drawings, allof which form a part of this disclosure. It is to be expresslyunderstood, however, that the drawings are for the purpose ofillustration and description only and are not intended to limit thescope of the present disclosure. It is understood that the drawings arenot to scale.

Provided herein are systems and components for an imaging system. Insome embodiments, the imaging system may include a single modalityimaging system and/or a multi-modality imaging system. The singlemodality imaging system may include, for example, a PET system, a SPECTsystem, or the like, or any combination thereof. The multi-modalityimaging system may include, for example, a positron emissiontomography-X-ray imaging (PET-X-ray) system, a single-photon emissioncomputed tomography-magnetic resonance imaging (SPECT-MRI) system, apositron emission tomography-computed tomography (PET-CT) system, adigital subtraction angiography-magnetic resonance imaging (DSA-MRI)system, etc. It should be noted that the imaging system described belowis merely provided for illustration purposes, and not intended to limitthe scope of the present disclosure.

The present disclosure provides mechanisms (which can include methods,systems, a computer-readable medium, etc.) for determining at least onecorrection parameter for a PET scanner. A phantom may be caused to movealong the long axis of the FOV of a PET scanner in a specific manner.For example, the phantom may be moved to a plurality of positions atpredetermined time intervals or continuously moved to the plurality ofpositions. Such a method may allow a phantom having a length that isless than the length of the FOV along the long axis of the FOV to beused to cover the whole FOV by moving the phantom. Thus, as compared tousing a long phantom whose length is the same as or close to the lengthof the FOV, the systems and methods provided by the present disclosureinvolving a relatively short phantom may be more convenient in terms oftransportation, storage, and/or and maneuver. Moreover, the cost ofmanufacturing such a relatively short phantom may also be reduced. Fordetermining the at least one correction parameter for each detector unitof the PET scanner, an actual sum of coincidence events (also referredto as a first sum of coincidence events) that are detected by thedetector unit may be determined based on scan data of the phantom. Areference sum of coincidence events (also referred to as a second sum ofcoincidence events) that are expected to be detected by the detectorunit under ideal conditions may also be determined. The at least onecorrection parameter may be determined based on the actual sum ofcoincidence events and the reference sum of coincidence events. Forexample, the at least one correction parameter may include an axialblock profile, a transverse block profile, a plane efficiency, a crystalefficiency, or the like, or any combination thereof.

FIG. 1 is a schematic diagram illustrating an exemplary imaging system100 according to some embodiments of the present disclosure. As shown,the imaging system 100 may include a imaging device 110, a network 120,one or more terminals 130, a processing device 140, and a storage device150. In some embodiments, the imaging device 110, the terminal(s) 130,the processing device 140, and/or the storage device 150 may beconnected to and/or communicate with each other via the network 120. Theconnection between the components of the imaging system 100 may bevariable. Merely by way of example, the imaging device 110 may beconnected to the processing device 140 through the network 120, asillustrated in FIG. 1. As another example, the imaging device 110 may beconnected to the processing device 140 directly. As a further example, aterminal 130 may be connected to the processing device 140 through thenetwork 120, as illustrated in FIG. 1, or connected to the processingdevice 140 directly.

The scanner (or referred to as the imaging device) 110 may generate orprovide image data via scanning a subject (e.g., a patient) disposed ona scanning couch of the imaging device 110. In some embodiments, theimaging device 110 may be a Positron Emission Tomography (PET) device, aSingle Photon Emission Computed Tomography (SPECT) device, a PositronEmission Tomography-Computed Tomography (PET-CT) device, a Single PhotonEmission Computed Tomography-Magnetic Resonance Imaging (SPECT-MRI)system, etc. In some embodiments, the subject may include a body, asubstance, an object, or the like, or a combination thereof. In someembodiments, the subject may include a specific portion of a body, suchas the head, the thorax, the abdomen, or the like, or a combinationthereof. In some embodiments, the subject may include a specific organor region of interest, such as an esophagus, a trachea, a bronchus, thestomach, the gallbladder, the small intestine, the colon, the bladder,the ureter, the uterus, a fallopian tube, etc.

In some embodiments, the imaging device 110 may include a gantry, adetector, an electronics module, a couch, and/or other components notshown, for example, a cooling assembly. The imaging device 110 may scana subject and obtain information related to the subject. The gantry maysupport components (e.g., the detectors) for detecting radiation eventsto generate an image. The couch may position a subject in a detectionregion. The detector may detect radiation events (e.g., gamma photons)emitted from the detection region. In some embodiments, the detector mayinclude a plurality of detector units. For example, a detector unit maybe a block including four photomultiplier tubes with a square ofsixty-four crystals. The detector units may be implemented in a suitablemanner, for example, a ring, a rectangle, or an array. In someembodiments, the detector unit may include one or more crystal elementsand/or one or more photomultiplier tubes (PMT) (not shown). In someembodiments, a PMT as employed in the present disclosure may be asingle-channel PMT or a multi-channel PMT. The electronics module maycollect and/or process electrical signals (e.g., scintillation pulses)generated by the detector. The electronics module may include an adder,a multiplier, a subtracter, an amplifier, a drive circuit, adifferential circuit, an integral circuit, a counter, a filter, ananalog-to-digital converter (ADC), a lower limit detection (LLD)circuit, a constant fraction discriminator (CFD) circuit, atime-to-digital converter (TDC), a coincidence circuit, or the like, orany combination thereof. In some embodiments, the detected radiationevents may be stored or archived in a storage (e.g., the storage device150), displayed on a display (e.g., a screen on a computing device), ortransferred to a connected device (e.g., an external database). In someembodiments, a user may control the imaging device 110 via the terminaldevice 130.

The network 120 may include any suitable network that can facilitate theexchange of information and/or data for the imaging system 100. In someembodiments, one or more components of the imaging system 100 (e.g., theimaging device 110, the processing device 140, the storage device 150,the terminal(s) 130) may communicate information and/or data with one ormore other components of the imaging system 100 via the network 120. Forexample, the processing device 140 may obtain image data from theimaging device 110 via the network 120. As another example, theprocessing device 140 may obtain user instruction(s) from theterminal(s) 130 via the network 120. The network 120 may be or include apublic network (e.g., the Internet), a private network (e.g., a localarea network (LAN)), a wired network, a wireless network (e.g., an802.11 network, a Wi-Fi network), a frame relay network, a virtualprivate network (VPN), a satellite network, a telephone network,routers, hubs, switches, server computers, and/or any combinationthereof. For example, the network 120 may include a cable network, awireline network, a fiber-optic network, a telecommunications network,an intranet, a wireless local area network (WLAN), a metropolitan areanetwork (MAN), a public telephone switched network (PSTN), a Bluetooth™network, a ZigBee™ network, a near field communication (NFC) network, orthe like, or any combination thereof. In some embodiments, the network120 may include one or more network access points. For example, thenetwork 120 may include wired and/or wireless network access points suchas base stations and/or internet exchange points through which one ormore components of the imaging system 100 may be connected to thenetwork 120 to exchange data and/or information.

The terminal(s) 130 may be connected to and/or communicate with theimaging device 110, the processing device 140, and/or the storage device150. For example, the terminal(s) 130 may obtain a processed image fromthe processing device 140. As another example, the terminal(s) 130 mayobtain image data acquired via the imaging device 110 and transmit theimage data to the processing device 140 to be processed. In someembodiments, the terminal(s) 130 may include a mobile device 131, atablet computer 132, a laptop computer 133, or the like, or anycombination thereof. For example, the mobile device 131 may include amobile phone, a personal digital assistant (PDA), a gaming device, anavigation device, a point of sale (POS) device, a laptop, a tabletcomputer, a desktop, or the like, or any combination thereof. In someembodiments, the terminal(s) 130 may include an input device, an outputdevice, etc. The input device may include alphanumeric and other keysthat may be input via a keyboard, a touch screen (for example, withhaptics or tactile feedback), a speech input, an eye-tracking input, abrain monitoring system, or any other comparable input mechanism. Theinput information received through the input device may be transmittedto the processing device 140 via, for example, a bus, for furtherprocessing. Other types of input devices may include a cursor controldevice, such as a mouse, a trackball, or cursor direction keys, etc. Theoutput device may include a display, a speaker, a printer, or the like,or a combination thereof. In some embodiments, the terminal(s) 130 maybe part of the processing device 140.

In some embodiments, the terminal(s) 130 may send and/or receive imagedata for image reconstruction to/from the processing device 140 via auser interface. The user interface may be in the form of an applicationfor image reconstruction implemented on the terminal(s) 130. The userinterface implemented on the terminal(s) 130 may be configured tofacilitate communication between a user and the processing device 140.In some embodiments, a user may input a request for determining at leastone correction parameter via the user interface implemented on theterminal(s) 130. In some embodiments, the terminal(s) 130 may send therequest for determining the at least one correction parameter to theprocessing device 140 for reconstructing an image based on a pluralityof target input functions as described elsewhere in the presentdisclosure (e.g., FIGS. 6-9 and the descriptions thereof).

The storage device 150 may store data, instructions, and/or any otherinformation. In some embodiments, the storage device 150 may store dataobtained from the processing device 140, the terminal(s) 130, and/or theimaging device 110. For example, the storage device 150 may store scandata obtained from the imaging device 110. As another example, thestorage device 150 may store one or more reconstructed images. In someembodiments, the storage device 150 may store data and/or instructionsthat the processing device 140 may execute or use to perform exemplarymethods described in the present disclosure. In some embodiments, thestorage device 150 may include a mass storage device, a removablestorage device, a volatile read-and-write memory, a read-only memory(ROM), or the like, or any combination thereof. Exemplary mass storagemay include a magnetic disk, an optical disk, a solid-state drive, etc.Exemplary removable storage may include a flash drive, a floppy disk, anoptical disk, a memory card, a zip disk, a magnetic tape, etc. Exemplaryvolatile read-and-write memory may include a random access memory (RAM).Exemplary RAM may include a dynamic RAM (DRAM), a double date ratesynchronous dynamic RAM (DDR SDRAM), a static RAM (SRAM), a thyristorRAM (T-RAM), and a zero-capacitor RAM (Z-RAM), etc. Exemplary ROM mayinclude a mask ROM (MROM), a programmable ROM (PROM), an erasableprogrammable ROM (EPROM), an electrically erasable programmable ROM(EEPROM), a compact disk ROM (CD-ROM), and a digital versatile disk ROM,etc. In some embodiments, the storage device 150 may be implemented on acloud platform as described elsewhere in the disclosure.

In some embodiments, the storage device 150 may be connected to thenetwork 120 to communicate with one or more other components of theimaging system 100 (e.g., the processing device 140, the terminal(s)130). One or more components of the imaging system 100 may access thedata or instructions stored in the storage device 150 via the network120. In some embodiments, the storage device 150 may be part of theprocessing device 140.

In some embodiments, a three-dimensional coordinate system may be usedin the imaging system 100 as illustrated in FIG. 1. A first axis may beparallel to the lateral direction of the couch (e.g., the X directionperpendicular to and pointing out of the paper as shown in FIG. 1). Asecond axis may be parallel to the longitudinal direction of the couch(e.g., the Z direction as shown in FIG. 1). The Z direction is alsoparallel to a long axis of the FOV of the imaging device 110. A thirdaxis may be along a vertical direction of the couch (e.g., the Ydirection as shown in FIG. 1). The origin of the three-dimensionalcoordinate system may be any point in the space. The origin of thethree-dimensional coordinate system may be determined by an operator.The origin of the three-dimensional coordinate system may be determinedby the imaging system 100.

The above description for FIG. 1 is intended to be illustrative, and notto limit the scope of the present disclosure. Many alternatives,modifications, and variations will be apparent to those skilled in theart. The features, structures, methods, and other characteristics of theexemplary embodiments described herein may be combined in various waysto obtain additional and/or alternative exemplary embodiments. Forexample, the storage device 150 may be a data storage including cloudcomputing platforms, such as public cloud, private cloud, community, andhybrid clouds, etc. However, those variations and modifications do notdepart the scope of the present disclosure.

FIG. 2 is a schematic diagram illustrating exemplary hardware and/orsoftware components of an exemplary computing device. In someembodiments, the processing device 140 may be implemented on thecomputing device 200. As illustrated in FIG. 2, the computing device 200may include a processor and a storage connected through a bus. Computerprograms may be stored in the storage (e.g., a non-volatile storagedevice). When the processor executes the computer programs, theprocessor may execute a method which will be described in connectionwith, for example, FIGS. 6-9. Optionally, the computing device mayfurther include a network interface, a display, and an input device. Theprocessor may be used to provide computing capabilities and generatecontrolling signals for controlling other components of the imagingsystem 100. The storage of the computing device may include anon-volatile storage medium and a memory. The non-volatile storagemedium may store an operating system and computer programs. The memorymay be used for executing the operating system and computer programs inthe non-volatile storage medium. The network interface of the computingdevice may be used to communicate with an external terminal through anetwork connection.

The processor may execute computer instructions (e.g., program code) andperform functions of the processing device 140 in accordance withtechniques described herein. The computer instructions may include, forexample, routines, programs, objects, components, data structures,procedures, modules, and functions, which perform particular functionsdescribed herein. For example, the processor may process image dataobtained from the imaging device 110, the terminals 130, the storagedevice 150, and/or any other component of the imaging system 100. Insome embodiments, the processor may include one or more hardwareprocessors, such as a microcontroller, a microprocessor, a reducedinstruction set computer (RISC), an application-specific integratedcircuits (ASICs), an application-specific instruction-set processor(ASIP), a central processing unit (CPU), a graphics processing unit(GPU), a physics processing unit (PPU), a microcontroller unit, adigital signal processor (DSP), a field-programmable gate array (FPGA),an advanced RISC machine (ARM), a programmable logic device (PLD), anycircuit or processor capable of executing one or more functions, or thelike, or any combinations thereof.

Merely for illustration, only one processor is described in thecomputing device 200. However, it should be noted that the computingdevice 200 in the present disclosure may also include multipleprocessors, and thus operations and/or method operations that areperformed by one processor as described in the present disclosure mayalso be jointly or separately performed by the multiple processors. Forexample, if in the present disclosure the processor of the computingdevice 200 executes both operation A and operation B, it should beunderstood that operation A and operation B may also be performed by twoor more different processors jointly or separately in the computingdevice 200 (e.g., a first processor executes operation A and a secondprocessor executes operation B, or the first and second processorsjointly execute operation s A and B).

The storage may store data/information obtained from the imaging device110, the terminals 130, the storage device 150, and/or any othercomponent of the imaging system 100. In some embodiments, the storagemay include a mass storage device, a removable storage device, avolatile read-and-write memory, a read-only memory (ROM), or the like,or any combination thereof. For example, the mass storage may include amagnetic disk, an optical disk, solid-state drives, etc. The removablestorage may include a flash drive, a floppy disk, an optical disk, amemory card, a zip disk, a magnetic tape, etc. The volatileread-and-write memory may include a random access memory (RAM). The RAMmay include a dynamic RAM (DRAM), a double date rate synchronous dynamicRAM (DDR SDRAM), a static RAM (SRAM), a thyristor RAM (T-RAM), and azero-capacitor RAM (Z-RAM), etc. The ROM may include a mask ROM (MROM),a programmable ROM (PROM), an erasable programmable ROM (EPROM), anelectrically erasable programmable ROM (EEPROM), a compact disk ROM(CD-ROM), and a digital versatile disk ROM, etc. In some embodiments,the storage may store one or more programs and/or instructions toperform exemplary methods described in the present disclosure. Forexample, the storage may store a program for the processing device 140for determining the position of a target region of a subject (e.g., atarget portion of a patient).

The input device may be used to input signals, data, information, etc.In some embodiments, the input device may enable user interaction withthe computing device 200. Examples of the input device may include akeyboard, a mouse, a touch screen, a microphone, or the like, or acombination thereof. Examples of the display may include a liquidcrystal display (LCD), a light-emitting diode (LED)-based display, aflat panel display, a curved screen, a television device, a cathode raytube (CRT), a touch screen, or the like, or a combination thereof.

The network interface may be connected to a network (e.g., the network120) to facilitate data communications. For example, the networkinterface may establish connections between the processing device 140and the imaging device 110, the terminals 130, and/or the storage device150. The connection may be a wired connection, a wireless connection,any other communication connection that can enable data transmissionand/or reception, and/or any combination of these connections. The wiredconnection may include, for example, an electrical cable, an opticalcable, a telephone wire, or the like, or any combination thereof. Thewireless connection may include, for example, a Bluetooth™ link, aWi-Fi™ link, a WiMax™ link, a WLAN link, a ZigBee™ link, a mobilenetwork link (e.g., 3G, 4G, 5G), or the like, or a combination thereof.In some embodiments, the network interface may be and/or include astandardized communication port, such as RS232, RS485, etc. In someembodiments, the network interface may be a specially designedcommunication port. For example, the network interface may be designedin accordance with the digital imaging and communications in medicine(DICOM) protocol.

It should be noted that the methods for determining at least onecorrection parameter provided in the present disclosure may beimplemented on a PET scanner correction apparatus. The PET scannercorrection apparatus may be implemented as part or all of the computingdevice 200 through software, hardware, or a combination thereof. In thefollowing description, as an example for description, the methods areimplemented on the computing device 200.

FIG. 3 is a schematic diagram illustrating exemplary hardware and/orsoftware components of an exemplary terminal device 300 according tosome embodiments of the present disclosure. As illustrated in FIG. 3,the terminal device 300 may include a communication platform 310, adisplay 320, a graphic processing unit (GPU) 330, a central processingunit (CPU) 340, an I/O 350, a memory 360, and a storage 390. In someembodiments, any other suitable component, including but not limited toa system bus or a controller (not shown), may also be included in theterminal device 300. In some embodiments, a mobile operating system 370(e.g., iOS™, Android™, Windows Phone™) and one or more applications 380may be loaded into the memory 360 from the storage 390 in order to beexecuted by the CPU 340. The applications 380 may include a browser orany other suitable mobile apps for receiving and rendering informationrelating to image processing or other information from the processingdevice 140. User interactions with the information stream may beachieved via the I/O 350 and provided to the processing device 140and/or other components of the imaging system 100 via the network 120.

To implement various modules, units, and their functionalities describedin the present disclosure, computer hardware platforms may be used asthe hardware platform(s) for one or more of the elements describedherein. A computer with user interface elements may be used to implementa personal computer (PC) or any other type of work station or terminaldevice. A computer may also act as a server if appropriately programmed.

FIG. 4 is a block diagram illustrating an exemplary PET scannercorrection device according to some embodiments of the presentdisclosure. As illustrated in FIG. 4, the PET scanner correction device400 may include a first obtaining module 410, a second obtaining module420, and a correction module 430. The modules may be hardware circuitsof all or part of the processing device 140. The modules may also beimplemented as an application or set of instructions read and executedby the processing device 140. Further, the modules may be anycombination of the hardware circuits and the application/instructions.For example, the modules may be part of the processing device 140 whenthe processing device 140 is executing the application/set ofinstructions.

The first obtaining module 410 may obtain, for each of the plurality ofdetector units of the imaging device 110, an actual sum of coincidenceevents. The actual sum of coincidence events (also referred to as afirst sum of coincidence events) may be determined based on scan data ofone or more scans of a phantom at a plurality of positions.

The second obtaining module 420 may obtain, for each of the plurality ofdetector units of the imaging device 110, a reference sum of coincidenceevents. In some embodiments, the reference sum of coincidence events(also referred to as a second sum of coincidence events) may representan expected sum of coincidence events under an ideal condition. As usedherein, the “ideal condition” refers to a condition that each gammaphoton emitted from the phantom is measured by the detector of the PETscanner. In some embodiments, for each of the plurality of positions, acount of coincidence events may be determined based on geometricparameters of the phantom, position information of the phantom, ascanning period of the phantom at the position, and informationregarding the tracer (e.g., a concentration, a half-life period). Thereference sum of coincidence events may be determined based on the countof coincidence events for each of the plurality of positions.

The correction module 430 may determine, for each of the plurality ofdetector units of the imaging device 110, at least one correctionparameter. In some embodiments, the at least one correction parametermay be determined based on the actual sum of coincidence events and thereference sum of coincidence events. For example, the at least onecorrection parameter may include an axial block profile, a transverseblock profile, a plane efficiency, a crystal efficiency, or the like, orany combination thereof. The detector of the PET scanner may include aplurality of detector units. A detector unit may be a block includingmultiple photomultiplier tubes with multiple crystals. In someembodiments, the at least one correction parameter may be determinedbased on a ratio of the actual sum of coincidence events to thereference sum of coincidence events. In some embodiments, the at leastone correction parameter may be determined based on a ratio of thereference sum of coincidence events to the actual sum of coincidenceevents. In some embodiments, after a correction parameter is determined,a corrected actual sum of coincidence events may be generated using thecorrection parameter. The corrected actual sum of coincidence events maybe used for determining another correction parameter.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations or modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. In someembodiments, the processing device 140 may include one or moreadditional modules. For example, the processing device 140 may furtherinclude a control module configured to control the movement of thephantom.

FIG. 5 is a block diagram illustrating an exemplary PET scannercorrection device according to some embodiments of the presentdisclosure. The modules may be hardware circuits of all or part of theprocessing device 140. The modules may also be implemented as anapplication or set of instructions read and executed by the processingdevice 140. Further, the modules may be any combination of the hardwarecircuits and the application/instructions. For example, the modules maybe part of the processing device 140 when the processing device 140 isexecuting the application/set of instructions.

As illustrated in FIG. 5, the first obtaining module 410 may include afirst obtaining unit 510, a first determination unit 515, and a secondobtaining unit 520. In some embodiments, the first obtaining unit 510may obtain scan data of one or more scans of the phantom at a pluralityof positions acquired by the detector. In some embodiments, the firstdetermination unit 515 may determine, for each of the plurality ofpositions, an actual count of coincidence events.

In some embodiments, the PET scanner correction device 500 may furtherinclude a processing module 570. Before determining the actual count ofcoincidence events for each of the plurality of positions, theprocessing module 570 can perform one or more corrections on the scandata of the phantom at the plurality of positions to obtain correctedscan data. The actual count of coincidence events may be determinedbased on the corrected scan data by the first determination unit 515.The one or more corrections may include at least one of an attenuationcorrection, a dead-time correction, a random coincidence correction, ascatter correction, or the like, or any combination thereof. In someembodiments, a Computed Tomography (CT) scan may be performed on thephantom for generating a CT image of the phantom. An image registrationoperation may be executed to align the CT image with each of theplurality of positions. At least one of the one or more corrections,such as the attenuation correction, may be performed based on the CTimage and the scan data.

The second obtaining module 420 may include a third obtaining unit 525and a fourth obtaining unit 530. In some embodiments, the thirdobtaining unit 525 may determine, for each of the plurality ofpositions, a count of coincidence events based on geometric parametersof the phantom, position information of the phantom, a scanning periodof the phantom at the position, and information regarding the tracer.The fourth obtaining unit 530 may determine the reference sum ofcoincidence events based on the count of coincidence events for each ofthe plurality of positions.

The correction module 430 may include a second determination unit 535, athird determination unit 540, a fourth determination unit 545, and afifth determination unit 550. The second determination unit 535 maydetermine the axial block profile based on the actual sum of coincidenceevents (i.e., the first sum of coincidence events) and the reference sumof coincidence events (i.e., the second sum of coincidence events). Thethird determination unit 540 may determine a first corrected sum ofcoincidence events by correcting the first sum of coincidence eventsusing the axial block profile and determining the plane efficiency basedon the first corrected sum of coincidence events and the reference sumof coincidence events. The fourth determination unit 545 may determine asecond corrected sum of coincidence events by correcting the firstcorrected sum of coincidence events using the plane efficiency anddetermining the transverse block profile determined based on the secondcorrected sum of coincidence events and the reference sum of coincidenceevents. The fifth determination unit 550 may determine a third correctedsum of coincidence events by correcting the second corrected sum ofcoincidence events using the transverse block profile and determiningthe crystal efficiency based on the third corrected sum of coincidenceevents and the reference sum of coincidence events.

In some embodiments, the PET scanner correction device 500 may furtherinclude a controlling module 560. The controlling module 560 may controlthe movement of the phantom along the long axis of the FOV of the PETscanner. For example, the controlling module 560 may control the couchof the PET scanner to move, thereby causing the position of the phantomwith respect to the FOV of the PET scanner to be changed.

It should be noted that the above description is merely provided for thepurposes of illustration, and not intended to limit the scope of thepresent disclosure. For persons having ordinary skills in the art,multiple variations or modifications may be made under the teachings ofthe present disclosure. However, those variations and modifications donot depart from the scope of the present disclosure. In someembodiments, any module mentioned above may be divided into two or moreunits. In some embodiments, the processing device 140 may include one ormore additional modules. For example, the processing device 140 mayfurther include a transmission module configured to transmit data (e.g.,the at least one correction parameter) for one or more components in theimaging system 100.

FIG. 6 is a flowchart illustrating an exemplary process for determiningat least one correction parameter according to some embodiments of thepresent disclosure. In some embodiments, the imaging device 110 (such asa PET scanner) may include a plurality of detector units. The process600 may be performed to determine the at least one correction parameterfor each of the plurality of detector units. At least a portion ofprocess 600 may be implemented on the computing device 200 asillustrated in FIG. 2, the terminal device 300 as illustrated in FIG. 3,and/or the PET scanner correction device 400 as illustrated in FIG. 4.In some embodiments, one or more operations of the process 600 may beimplemented in the imaging system 100 as illustrated in FIG. 1. In someembodiments, one or more operations in the process 600 may be stored inthe storage device 150 and/or the storage of the computing device 200(e.g., an ROM, an RAM, etc.) in the form of instructions, and invokedand/or executed by the processing device 140, or the processor of thecomputing device 200. In some embodiments, the instructions may betransmitted to one or more components of the system 100 in the form ofelectronic current or electrical signals.

In 602, an actual sum of coincidence events may be obtained. In someembodiments, the first obtaining module 410 may perform operation 602for each of the plurality of detector units of the PET scanner. For eachof the plurality of detector units, the actual sum of coincidence events(also referred to as a first sum of coincidence events) that aredetected by the detector unit may be determined based on scan data ofone or more scans of a phantom at a plurality of positions.

In some embodiments, the length of the phantom may be less than thelength of the FOV of the PET scanner along the long axis of the FOV (theZ direction as illustrated in FIG. 1). For brevity, the long axis of theFOV of the PET scanner may be referred to as the axis, unless otherwisestated. The phantom may have a cavity. The cavity may contain a PETtracer (e.g., in the form of a tracer solution), which may be used as aradiation source. The phantom may be placed in the FOV (e.g., placed onthe couch of the PET scanner) and moved along the axis of the FOV. Insome embodiments, the phantom may be fixed on the couch and caused tomove by the movement of the couch. In some embodiments, the phantom maybe caused to move by other movement controlling devices. For instance,the phantom may be driven by a motor to move along a sliding railmounted on the top of the couch.

In some embodiments, the phantom may move discontinuously to theplurality of positions, for example, at predetermined time intervals.Multiple scans may be performed on the phantom at different positions.Merely by way of example, the phantom may move in a step-wise mode. Forinstance, the phantom may be moved to a first position of the pluralityof positions and pause at the first position. A scan may be performed onthe phantom at the first position. Then the phantom may be moved to asecond position of the plurality of positions and pause at the secondposition. Another scan may be performed on the phantom at the secondposition. In some embodiments, the distance between two neighboringpositions next to each other along the axis of the FOV may vary. As usedherein, two positions where the phantom pauses and scans are performedare considered neighboring positions if they are next to each otheralong the axis of the FOV. In some embodiments, the distance between twoneighboring positions may be a constant value.

A region that the phantom occupies in the FOV of the PET scanner at aposition may be referred to as a sub-region of the FOV. As used herein,two sub-regions of the FOV where the phantom occupies are consideredneighboring sub-regions if they are next to each other along the axis ofthe FOV. In some embodiments, at least two neighboring sub-regions ofthe FOV corresponding to two neighboring positions of the plurality ofpositions may overlap. For each movement, the phantom may be moved for amoving distance that is less than the length of the phantom. In someembodiments, at least two neighboring sub-regions of the FOVcorresponding to neighboring positions of the plurality of positions donot overlap.

In some embodiments, the phantom may move continuously to a plurality ofpositions at varying speeds or a constant speed. A single scan may beperformed on the phantom during the continuous movement of the phantom.For example, the phantom may move continuously at 3 millimeters(mm)/second (s), 5 mm/s, 8 mm/s, etc.

By the continuous or discontinuous movement of the phantom, the one ormore scans of the phantom can cover the entire FOV of the PET scanner ora portion thereof. Thus, the scan data of the one or more scans may beused for determining at least one correction parameter associated withthe PET scanner or the covered portion thereof.

As described in FIG. 1, the imaging system 100 may include the imagingdevice 110 (e.g., a PET scanner) and the processing device 140. Theprocessing device 140 may be operably connected to the imaging device110. The processing device 140 may obtain the scan data of the phantomat each position which is acquired by the PET scanner and then determinethe actual sum of coincidence events. Optionally, the scan data of thephantom acquired by the PET scanner at each position may be stored in astorage device (e.g., the storage device 150 shown in FIG. 1).Alternatively or additionally, the scan data may be stored in theprocessing device 140 and/or the terminal device 130. In someembodiments, the scan data may be stored in the form of list mode dataor sinogram data.

In 604, a reference sum of coincidence events may be obtained. In someembodiments, operation 604 may be performed by the second obtainingmodule 420. In some embodiments, the reference sum of coincidence events(also referred to as a second sum of coincidence events) may representan expected sum of coincidence events that the detector unit is expectedto detect under an ideal condition. As used herein, the “idealcondition” refers to a condition that each pair of gamma-photons emittedin a back-to-back manner due to the annihilation of positron-electronpairs without interacting with other substances and reach the detectorsurface are detected by the detector of the PET scanner. In someembodiments, for each of the plurality of positions, an expected countof coincidence events (also referred to as a second count of coincidenceevents) under the ideal condition may be determined based on geometricparameters of the phantom, position information of the phantom, ascanning period of the phantom at the position, and informationregarding the tracer (e.g., a concentration, a half-life period). Thereference sum of coincidence events may be determined based on theexpected count of coincidence events for each of the plurality ofpositions.

In 606, at least one correction parameter may be determined based on theactual sum of coincidence events and the reference sum of coincidenceevents. In some embodiments, operation 606 may be performed by thecorrection module 430. The at least one correction parameter may be usedfor correcting the detecting efficiency for each of the plurality ofdetector units of the PET scanner. For example, the at least onecorrection parameter may include an axial block profile, a transverseblock profile, a plane efficiency, a crystal efficiency, or the like, orany combination thereof. The detector of the PET scanner may include aplurality of detector units. The axial block profile and the transverseblock profile may be used for compensating for the sensitivitydistribution caused by the position inside the block detector (e.g., dueto the gap between two neighbouring blocks). The plane efficiency may beused for compensating for the sensitivity distribution caused by theincident angle of the photon with respect to the surface of the detector(e.g., due to an incident angle other than 90° to the surface of thedetector on which the photon impinges). The crystal efficiency may beused for compensating for the sensitivity distribution caused bydifferences in the properties of the detector crystals (e.g., due toimpurities or non-uniformity of the crystals). In some embodiments, theat least one correction parameter may be determined based on a ratio ofthe actual sum of coincidence events to the reference sum of coincidenceevents. In some embodiments, the at least one correction parameter maybe determined based on a ratio of the reference sum of coincidenceevents to the actual sum of coincidence events. In some embodiments,after a correction parameter is determined, a corrected actual sum ofcoincidence events may be generated using the correction parameter. Thecorrected actual sum of coincidence events may be used for determininganother correction parameter. More description regarding thedetermination of the at least one correction parameter may be foundelsewhere in the present disclosure, for example, in FIG. 9 and thedescription thereof.

In some embodiments, after a PET scan is performed on a subject (e.g., apatient, an animal), or a portion thereof, scan data of the scan may becorrected using the at least one correction parameter. A PET image maybe reconstructed based on the corrected scan data. The correction usingthe at least one correction parameter may improve the quality of the PETimage and provide more accurate information associated with the subject.

It should be noted that the above description regarding the process 600is merely provided for the purposes of illustration, and not intended tolimit the scope of the present disclosure. For persons having ordinaryskills in the art, multiple variations or modifications may be madeunder the teachings of the present disclosure. However, those variationsand modifications do not depart from the scope of the presentdisclosure.

FIG. 7 is a flowchart illustrating an exemplary process for determiningan actual sum of coincidence events according to some embodiments of thepresent disclosure. At least a portion of process 700 may be implementedon the computing device 200 as illustrated in FIG. 2, the terminaldevice 300 as illustrated in FIG. 3, and/or the PET scanner correctiondevice 400 as illustrated in FIG. 4. In some embodiments, one or moreoperations of the process 700 may be implemented in the imaging system100 as illustrated in FIG. 1. In some embodiments, one or moreoperations in the process 700 may be stored in the storage device 150and/or the storage of the computing device 200 (e.g., an ROM, an RAM,etc.) in the form of instructions, and invoked and/or executed by theprocessing device 140, or the processor of the computing device 200. Insome embodiments, the instructions may be transmitted to one or morecomponents of the system 100 in the form of electronic current orelectrical signals.

In 702, scan data of one or more scans of the phantom at a plurality ofpositions acquired by the detector are obtained. In some embodiments,operation 702 may be performed by the first obtaining unit 510 of thefirst obtaining module 410. In some embodiment, operation 702 may beperformed in a similar manner as operation 602, the description of whichis not repeated here.

In 704, for each of the plurality of positions, an actual count ofcoincidence events (also referred to as a first count of coincidenceevents) may be determined. In some embodiments, operation 704 may beperformed by the first determination unit 515 of the first obtainingmodule 410. In some embodiments, before determining the actual count ofcoincidence events for each of the plurality of positions for thedetector unit, the computing device 200 can perform one or morecorrections on the scan data of the phantom at the plurality ofpositions to obtain corrected scan data. The actual count of coincidenceevents may be determined based on the corrected scan data. The one ormore corrections may include at least one of an attenuation correction,a dead-time correction, a random coincidence correction, a scattercorrection, or the like, or any combination thereof. In someembodiments, a Computed Tomography (CT) scan may be performed on thephantom for generating a CT image of the phantom. An image registrationoperation may be executed to align the CT image with each of theplurality of positions. At least one of the one or more corrections,such as the attenuation correction, may be performed based on the CTimage and the scan data.

In 706, the actual sum of coincidence events may be determined by addingup the count of coincidence events for each of the plurality ofpositions. In some embodiments, operation 706 may be performed by thesecond obtaining unit 520 of the first obtaining module 410. In someembodiments, the actual sum of coincidence events may be a weighted sumof the count of coincidence events for each of the plurality ofpositions. For instance, a weight of an oblique LOR may be higher than aweight of a vertical LOR. The angle between the vertical LOR and a pairof corresponding detector units may be 90°. The angle between theoblique LOR and a pair of corresponding detector units may be other than90°. Since a pair of gamma photons relating to the oblique LOR maytravel a longer distance to reach the detector as compared to thevertical LOR, assigning a higher weight to the oblique LOR may improvethe accuracy of the determination of the actual sum of coincidence.

It should be noted that the above description regarding the process 700is merely provided for the purposes of illustration, and not intended tolimit the scope of the present disclosure. For persons having ordinaryskills in the art, multiple variations or modifications may be madeunder the teachings of the present disclosure. However, those variationsand modifications do not depart from the scope of the presentdisclosure.

FIG. 8 is a flowchart illustrating an exemplary process for determininga reference sum of coincidence events according to some embodiments ofthe present disclosure. At least a portion of process 800 may beimplemented on the computing device 200 as illustrated in FIG. 2, theterminal device 300 as illustrated in FIG. 3, and/or the PET scannercorrection device 400 as illustrated in FIG. 4. In some embodiments, oneor more operations of the process 800 may be implemented in the imagingsystem 100 as illustrated in FIG. 1. In some embodiments, one or moreoperations in the process 800 may be stored in the storage device 150and/or the storage of the computing device 200 (e.g., an ROM, an RAM,etc.) in the form of instructions, and invoked and/or executed by theprocessing device 140, or the processor of the computing device 200. Insome embodiments, the instructions may be transmitted to one or morecomponents of the system 100 in the form of electronic current orelectrical signals.

In 802, for each of the plurality of positions, an expected count ofcoincidence events may be determined based on geometric parameters ofthe phantom, position information of the phantom, and a scanning periodof the phantom at the position. In some embodiments, other factors mayalso be considered when determining the expected count of coincidenceevents, such as information regarding the tracer. In some embodiments,the second obtaining module 420 (e.g., the third obtaining unit 525) mayperform operation 802 for each of the plurality of detector units of thePET scanner. For example, the geometric parameters may include the shapeand the dimensions of the phantom. The position information of thephantom may refer to a spatial location of the phantom relative to thegantry of the imaging system 100. For example, the position of thephantom may be described using the position of a central point of thephantom. In some embodiments, the position information of the phantommay be determined based on the couch position with respect to the PETscanner when the phantom is caused to move by the movement of the couch.In some embodiments, for a discontinuous movement of the phantom (thatis, the phantom pauses after reaching one of the plurality ofpositions), the scanning period refers to a duration of a scan on thephantom at a position. In some embodiments, for a continuous movement ofthe phantom (that is, the phantom keeps moving without pausing at anyone of the plurality of positions), the scanning period refers to anaverage duration of a portion of the scan on the phantom when thephantom is in the vicinity of the position.

In 804, the reference sum of coincidence events may be determined basedon the expected count of coincidence events for each of the plurality ofpositions. In some embodiments, the second obtaining module 420 (e.g.,the fourth obtaining unit 530) may perform operation 804 for each of theplurality of detector units of the PET scanner.

It should be noted that the above description regarding the process 600is merely provided for the purposes of illustration, and not intended tolimit the scope of the present disclosure. For persons having ordinaryskills in the art, multiple variations or modifications may be madeunder the teachings of the present disclosure. However, those variationsand modifications do not depart from the scope of the presentdisclosure.

FIG. 9 is a flowchart illustrating an exemplary process for determiningat least one correction parameter according to some embodiments of thepresent disclosure. In some embodiments, for each of the plurality ofdetector units of the PET scanner, the at least one correction parametermay be determined. At least a portion of process 900 may be implementedon the computing device 200 as illustrated in FIG. 2, the terminaldevice 300 as illustrated in FIG. 3, and/or the PET scanner correctiondevice 400 as illustrated in FIG. 4. In some embodiments, one or moreoperations of the process 900 may be implemented in the imaging system100 as illustrated in FIG. 1. In some embodiments, one or moreoperations in the process 900 may be stored in the storage device 150and/or the storage of the computing device 200 (e.g., an ROM, an RAM,etc.) in the form of instructions, and invoked and/or executed by theprocessing device 140, or the processor of the computing device 200. Insome embodiments, the instructions may be transmitted to one or morecomponents of the system 100 in the form of electronic current orelectrical signals.

In 902, an axial block profile may be determined based on the actual sumof coincidence events (i.e., the first sum of coincidence events) andthe reference sum of coincidence events (i.e., the second sum ofcoincidence events). In some embodiments, operation 902 may be performedby the correction module 430 (e.g., the second determination unit 535).In some embodiments, the axial block profile may be determined based ona ratio of the actual sum of coincidence events to the reference sum ofcoincidence events. In some embodiments, the axial block profile may bedetermined based on a ratio of the reference sum of coincidence eventsto the actual sum of coincidence events.

In 904, a first corrected sum of coincidence events may be obtained bycorrecting the first sum of coincidence events using the axial blockprofile, and the plane efficiency may be determined based on the firstcorrected sum of coincidence events and the reference sum of coincidenceevents. In some embodiments, operation 902 may be performed by thecorrection module 430 (e.g., the third determination unit 540). In someembodiments, to obtain the first corrected sum of coincidence events,the scan data may be transformed, for example, by decreasing one or moredimensions of the scan data to focus on the impact of the planeefficiency. In some embodiments, the plane efficiency may be determinedbased on a ratio of the first corrected sum of coincidence events to thereference sum of coincidence events. In some embodiments, the planeefficiency may be determined based on a ratio of the reference sum ofcoincidence events to the first corrected sum of coincidence events.

In 906, a second corrected sum of coincidence events may be obtained bycorrecting the first corrected sum of coincidence events using the planeefficiency, and the transverse block profile may be determined based onthe second corrected sum of coincidence events and the reference sum ofcoincidence events. In some embodiments, operation 902 may be performedby the correction module 430 (e.g., the fourth determination unit 545).In some embodiments, to obtain the second corrected sum of coincidenceevents, the scan data may be transformed, for example, by decreasing oneor more dimensions of the scan data to focus on the impact of thetransverse block profile. In some embodiments, the transverse blockprofile may be determined based on a ratio of the second corrected sumof coincidence events to the reference sum of coincidence events. Insome embodiments, the transverse block profile may be determined basedon a ratio of the reference sum of coincidence events to the secondcorrected sum of coincidence events.

In 908, a third corrected sum of coincidence events may be obtained bycorrecting the second corrected sum of coincidence events using thetransverse block profile, and the crystal efficiency may be determinedbased on the third corrected sum of coincidence events and the referencesum of coincidence events. In some embodiments, operation 902 may beperformed by the correction module 430 (e.g., the fifth determinationunit 550). In some embodiments, to obtain the third corrected sum ofcoincidence events, the scan data may be transformed, for example, bydecreasing one or more dimensions of the scan data to focus on theimpact of the crystal efficiency. In some embodiments, the crystalefficiency may be determined based on a ratio of the third corrected sumof coincidence events to the reference sum of coincidence events. Insome embodiments, the crystal efficiency may be determined based on aratio of the reference sum of coincidence events to the third correctedsum of coincidence events.

Such a process for determining the correction parameters may improve theaccuracy of the correction parameters, and thus improving the quality ofa PET image reconstructed using the correction parameters. It should benoted that the order for determining the correction parameters are notlimited by the present disclosure. For example, the transverse blockprofile may be determined before the plane efficiency is determined. Insome embodiments, the determination for one or more correctionparameters may be omitted, such as the plane efficiency.

Having thus described the basic concepts, it may be rather apparent tothose skilled in the art after reading this detailed disclosure that theforegoing detailed disclosure is intended to be presented by way ofexample only and is not limiting. Various alterations, improvements, andmodifications may occur and are intended to those skilled in the art,though not expressly stated herein. These alterations, improvements, andmodifications are intended to be suggested by this disclosure and arewithin the spirit and scope of the exemplary embodiments of thisdisclosure.

Moreover, certain terminology has been used to describe embodiments ofthe present disclosure. For example, the terms “one embodiment,” “anembodiment,” and “some embodiments” mean that a particular feature,structure or characteristic described in connection with the embodimentis included in at least one embodiment of the present disclosure.Therefore, it is emphasized and should be appreciated that two or morereferences to “an embodiment” or “one embodiment” or “an alternativeembodiment” in various portions of this specification are notnecessarily all referring to the same embodiment. Furthermore, theparticular features, structures or characteristics may be combined assuitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects ofthe present disclosure may be illustrated and described herein in any ofa number of patentable classes or context including any new and usefulprocess, machine, manufacture, or composition of matter, or any new anduseful improvement thereof. Accordingly, aspects of the presentdisclosure may be implemented entirely hardware, entirely software(including firmware, resident software, micro-code, etc.) or combiningsoftware and hardware implementation that may all generally be referredto herein as a “module,” “unit,” “component,” “device,” or “system.”Furthermore, aspects of the present disclosure may take the form of acomputer program product embodied in one or more computer-readable mediahaving computer-readable program code embodied thereon.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including electro-magnetic, optical, or thelike, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that may communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device. Program code embodied on acomputer readable signal medium may be transmitted using any appropriatemedium, including wireless, wireline, optical fiber cable, RF, or thelike, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET,Python or the like, conventional procedural programming languages, suchas the “C” programming language, Visual Basic, Fortran 2003, Perl, COBOL2002, PHP, ABAP, dynamic programming languages such as Python, Ruby, andGroovy, or other programming languages. The program code may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider) or in a cloud computing environment or offered as aservice such as a Software as a Service (SaaS).

Furthermore, the recited order of processing elements or sequences, orthe use of numbers, letters, or other designations therefore, is notintended to limit the claimed processes and methods to any order exceptas may be specified in the claims. Although the above disclosurediscusses through various examples what is currently considered to be avariety of useful embodiments of the disclosure, it is to be understoodthat such detail is solely for that purpose and that the appended claimsare not limited to the disclosed embodiments, but, on the contrary, areintended to cover modifications and equivalent arrangements that arewithin the spirit and scope of the disclosed embodiments. For example,although the implementation of various components described above may beembodied in a hardware device, it may also be implemented as a softwareonly solution, e.g., an installation on an existing server or mobiledevice.

Similarly, it should be appreciated that in the foregoing description ofembodiments of the present disclosure, various features are sometimesgrouped together in a single embodiment, figure, or description thereoffor the purpose of streamlining the disclosure aiding in theunderstanding of one or more of the various embodiments. This method ofdisclosure, however, is not to be interpreted as reflecting an intentionthat the claimed subject matter requires more features than areexpressly recited in each claim. Rather, claim subject matter lie inless than all features of a single foregoing disclosed embodiment.

1. A system for determining at least one correction parameter for aPositron Emission Tomography (PET) scanner including a plurality ofdetector units, comprising: at least one non-transitory storage mediumincluding a set of instructions; and at least one processor incommunication with the at least one non-transitory storage medium,wherein when executing the set of instructions, the at least oneprocessor is configured to cause the system to perform operationsincluding: for each of the plurality of detector units, determining,based on scan data of one or more scans of a phantom at a plurality ofpositions, a first sum of coincidence events detected by the detectorunit, wherein the phantom is moved to the plurality of positions alongan axis of a field of view of the PET scanner during the one or morescans, and a length of the phantom is less than a length of the field ofview of the PET scanner along the axis; determining a second sum ofcoincidence events that are expected to be detected by the detectorunit; and determining, based on the first sum of coincidence events andthe second sum of coincidence events, at least one correction parameterassociated with the detector unit.
 2. The system of claim 1, wherein todetermine the first sum of coincidence events, the at least oneprocessor is configured to cause the system to perform operationsincluding: obtaining the scan data of the one or more scans of thephantom at the plurality of positions; for each of the plurality ofpositions, determining, based on the scan data, a first count ofdetected coincidence events that are detected by the detector unit; anddetermining the first sum of coincidence events based on the first countof detected coincidence events for each of the plurality of positions.3. The system of claim 1, wherein to determine the second sum ofcoincidence events, the at least one processor is configured to causethe system to perform operations including: for each of the plurality ofpositions, determining a second count of coincidence events that areexpected to be detected by the detector unit based on geometricparameters of the phantom, position information of the phantom, and ascanning period of the phantom at the position; and determining thesecond sum of coincidence events based on the second count ofcoincidence events for each of the plurality of positions.
 4. The systemof claim 1, wherein the phantom is moved to the plurality of positionsin a step-wise mode, and a moving distance for each movement of thephantom is less than the length of the phantom.
 5. The system of claim1, wherein the phantom is continuously moved to the plurality ofpositions.
 6. (canceled)
 7. The system of claim 1, wherein to determinethe first sum of coincidence events, the at least one processor isconfigured to cause the system to perform operations including:performing one or more corrections on the scan data of the one or morescans of the phantom at the plurality of positions to obtain correctedscan data, wherein the one or more corrections include at least one ofan attenuation correction, a dead-time correction, a random coincidencecorrection, or a scatter correction; and determining the first sum ofcoincidence events based on the corrected scan data.
 8. The system ofclaim 1, wherein the at least one correction parameter includes an axialblock profile, and to determine the at least one correction parameter,the at least one processor is configured to cause the system to performoperations including: determining the axial block profile associatedwith the PET scanner based on the first sum of coincidence events andthe second sum of coincidence events.
 9. The system of claim 8, whereinthe at least one correction parameter includes a plane efficiency, andto determine the at least one correction parameter, the at least oneprocessor is configured to cause the system to perform operationsincluding: obtaining a first corrected sum of coincidence events bycorrecting the first sum of coincidence events using the axial blockprofile for each detector unit; and determining the plane efficiencyassociated with the PET scanner based on the first corrected sum ofcoincidence events and the second sum of coincidence events.
 10. Thesystem of claim 9, wherein the at least one correction parameterincludes a transverse block profile, and to determine the at least onecorrection parameter, the at least one processor is further configuredto cause the system to perform operations including: obtaining a secondcorrected sum of coincidence events by correcting the first correctedsum of coincidence events using the plane efficiency for each detectorunit; and determining the transverse block profile associated with thePET scanner based on the second corrected sum of coincidence events andthe second sum of coincidence events.
 11. The system of claim 10,wherein the at least one correction parameter includes a crystalefficiency, and to determine the at least one correction parameter, theat least one processor is configured to cause the system to performoperations including: obtaining a third corrected sum of coincidenceevents by correcting the second corrected sum of coincidence eventsusing the transverse block profile for each detector unit; anddetermining the crystal efficiency associated with the PET scanner basedon the third corrected sum of coincidence events and the second sum ofcoincidence events.
 12. A method for determining at least one correctionparameter for a Positron Emission Tomography (PET) scanner including aplurality of detector units, implemented on a computing device having atleast one processor and at least one non-transitory storage medium, themethod comprising: for each of the plurality of detector units,determining, based on scan data of one or more scans of a phantom at aplurality of positions, a first sum of coincidence events detected bythe detector unit, wherein the phantom is moved to the plurality ofpositions along an axis of a field of view of the PET scanner during theone or more scans, and a length of the phantom is less than a length ofthe field of view of the PET scanner along the axis; determining asecond sum of coincidence events that are expected to be detected by thedetector unit; and determining, based on the first sum of coincidenceevents and the second sum of coincidence events, at least one correctionparameter associated with the detector unit.
 13. The method of claim 12,wherein determining the first sum of coincidence events includes:obtaining the scan data of the one or more scans of the phantom at theplurality of positions; for each of the plurality of positions,determining, based on the scan data, a first count of detectedcoincidence events that are detected by the detector unit; anddetermining the first sum of coincidence events based on the first countof detected coincidence events for each of the plurality of positions.14. The method of claim 12, wherein determining the second sum ofcoincidence events includes: for each of the plurality of positions,determining a second count of coincidence events that are expected to bedetected by the detector unit based on geometric parameters of thephantom, position information of the phantom, and a scanning period ofthe phantom at the position; and determining the second sum ofcoincidence events based on the second count of coincidence events foreach of the plurality of positions.
 15. The method of claim 12, whereinthe phantom is moved to the plurality of positions in a step-wise mode,and a moving distance for each movement of the phantom is less than thelength of the phantom.
 16. (canceled)
 17. (canceled)
 18. The method ofclaim 12, wherein determining the first sum of coincidence eventsincludes: performing one or more corrections on the scan data of the oneor more scans of the phantom at the plurality of positions to obtaincorrected scan data, wherein the one or more corrections include atleast one of an attenuation correction, a dead-time correction, a randomcoincidence correction, or a scatter correction; and determining thefirst sum of coincidence events based on the corrected scan data. 19.The method of claim 12, wherein the at least one correction parameterincludes an axial block profile, and determining the at least onecorrection parameter includes: determining the axial block profileassociated with the PET scanner based on the first sum of coincidenceevents and the second sum of coincidence events.
 20. The method of claim19, wherein the at least one correction parameter includes a planeefficiency, and determining the at least one correction parameterfurther includes: obtaining a first corrected sum of coincidence eventsby correcting the first sum of coincidence events using the axial blockprofile for each detector unit; and determining the plane efficiencyassociated with the PET scanner based on the first corrected sum ofcoincidence events and the second sum of coincidence events.
 21. Themethod of claim 20, wherein the at least one correction parameterincludes a transverse block profile, and determining the at least onecorrection parameter further includes: obtaining a second corrected sumof coincidence events by correcting the first corrected sum ofcoincidence events using the plane efficiency for each detector unit;and determining the transverse block profile associated with the PETscanner based on the second corrected sum of coincidence events and thesecond sum of coincidence events.
 22. The method of claim 21, whereinthe at least one correction parameter includes a crystal efficiency, anddetermining the at least one correction parameter further includes:obtaining a third corrected sum of coincidence events by correcting thesecond corrected sum of coincidence events using the transverse blockprofile for each detector unit; and determining the crystal efficiencyassociated with the PET scanner based on the third corrected sum ofcoincidence events and the second sum of coincidence events.
 23. Anon-transitory computer readable medium, comprising at least one set ofinstructions, wherein when executed by at least one processor of acomputing device, the at least one set of instructions direct the atleast one processor to perform operations including: for each of theplurality of detector units, determining, based on scan data of one ormore scans of a phantom at a plurality of positions, a first sum ofcoincidence events detected by the detector unit, wherein the phantom ismoved to the plurality of positions along an axis of a field of view ofthe PET scanner during the one or more scans, and a length of thephantom is less than a length of the field of view of the PET scanneralong the axis; determining a second sum of coincidence events that areexpected to be detected by the detector unit; and determining, based onthe first sum of coincidence events and the second sum of coincidenceevents, at least one correction parameter associated with the detectorunit.